Astaxanthin Exerts Anabolic Effects via Pleiotropic Modulation of the Excitable Tissue

Astaxanthin is a lipid-soluble carotenoid influencing lipid metabolism, body weight, and insulin sensitivity. We provide a systematic analysis of acute and chronic effects of astaxanthin on different organs. Changes by chronic astaxanthin feeding were analyzed on general metabolism, expression of regulatory proteins in the skeletal muscle, as well as changes of excitation and synaptic activity in the hypothalamic arcuate nucleus of mice. Acute responses were also tested on canine cardiac muscle and different neuronal populations of the hypothalamic arcuate nucleus in mice. Dietary astaxanthin significantly increased food intake. It also increased protein levels affecting glucose metabolism and fatty acid biosynthesis in skeletal muscle. Inhibitory inputs innervating neurons of the arcuate nucleus regulating metabolism and food intake were strengthened by both acute and chronic astaxanthin treatment. Astaxanthin moderately shortened cardiac action potentials, depressed their plateau potential, and reduced the maximal rate of depolarization. Based on its complex actions on metabolism and food intake, our data support the previous findings that astaxanthin is suitable for supplementing the diet of patients with disturbances in energy homeostasis.

Introduction
Astaxanthin (AX) is a safe, lipid-soluble, bioavailable natural carotenoid compound present in several microorganisms and various aquatic and nonaquatic species including crustaceans, fish or the flamingo. A major source of AX is Haematococcus pluvialis, a green microalga with high AX content [1][2][3][4]. AX is a potent nutraceutical widely used as a nutritional supplement with antioxidant and anticancer actions. AX was shown to prevent diabetes, cardiovascular diseases, neurodegenerative disorders, and stimulate immunization [5,6]. As an antioxidant, AX reduces oxidative stress, increases the bioavailability of nitric oxide (NO) and the activity of antioxidant enzymes, and maintains the rheological properties of the blood [7]. It ameliorates skeletal muscle atrophy, and it exerts neuroprotective actions [8,9]. AX's anti-inflammatory properties involve modulating the

Actions of Astaxanthin Feeding on Metabolism and Food Intake
At first, the basic metabolic changes of control and AX fed mice were determined. Cumulative O 2 usage was similar before and after the four weeks of special feeding both in control and AX group ( Figure 1A); however, when these parameters were normalized to the actual body weight, a significant decrease was observed following the treatment in both groups ( Figure 1B). There was no significant difference between O 2 usage of control and AX groups. Similar observation was done regarding cumulative CO 2 production ( Figure 1C), and its normalized values ( Figure 1D). More specifically, average cumulative food intake revealed to be significantly higher in AX group compared to its control counterpart following 4 weeks of special feeding. Furthermore, food intake increased significantly after the treatment within the AX group ( Figure 1E), while this parameter was similar in control animals before and after 4 weeks of feeding. Altogether, the average body weight changes in the AX group were significantly higher as compared to the control group ( Figure 1F).
Activity (X amb and X total ) was significantly reduced in both control and AX groups after 4 weeks of feeding. Other parameters involved in the overall metabolism measured in vivo were either lower (VO 2 and VCO 2 ), higher (cumulative water intake), or similar (RER, heat production, sleeping time) when comparing the data of control and AX animals before and after the 4 weeks of feeding. However, one must note that overall significant alterations were not observed as a consequence of the effect of AX administration (Table S1). Time-dependent changes of all the aforementioned parameters are plotted and presented in Figure S1A-F. Data from four individual measured points (equal with 72 min) were averaged in all animals within the same groups and were plotted as a function of time. . Gray column: control group before sham feeding (C); hollow column: control group after sham feeding (S); black column: AX fed group before feeding of astaxanthin-containing chow (C); red column: AX fed group after feeding of astaxanthincontaining chow (AX). All panels have the same arrangement as above; (C,D) Effects on CO2 consumption without (C) and with normalization on body weight (D); (E) Normalized actions on food intake; (F) Changes in body weight gain. * denotes significant differences at p < 0.05. Activity (Xamb and Xtotal) was significantly reduced in both control and AX groups after 4 weeks of feeding. Other parameters involved in the overall metabolism measured in vivo were either lower (VO2 and VCO2), higher (cumulative water intake), or similar (RER, heat production, sleeping time) when comparing the data of control and AX animals before and after the 4 weeks of feeding. However, one must note that overall significant alterations were not observed as a consequence of the effect of AX administration (Table S1). Time-dependent changes of all the aforementioned parameters are plotted and presented in Figure S1A-F. Data from four individual measured points (equal with 72 min) were averaged in all animals within the same groups and were plotted as a function of time.
Using the respiratory ratio (VCO2/VO2), we calculated the calorific value (CV) using the equation (CV = 3.815 × 1.232 × RER), then total energy expenditure (TEE) was determined by multiplying CV and VO2. Subtracting resting/basal metabolic rate (RMR) from TEE we got the activity related energy expenditure (TEEactivity). Both versions of energy expenditure are plotted as a function of time ( Figure S1G,H, respectively).
In summary, mice kept on AX supplemented diet had increased food intake compared to the control group. In line with this, parameters related to in vivo metabolic activity did not change following the four weeks of special AX feeding.

Astaxanthin Feeding Influences the Activation of Signaling Molecules Affecting Skeletal Muscle Metabolism
Skeletal muscles are responsible for a significant proportion of metabolism of the whole organism; therefore, we aimed to investigate whether proteins regulating skeletal muscle metabolism are affected by the AX diet. AX was shown to accumulate in skeletal muscle [30]; therefore, the effects of long-term AX administration on representative muscles known to be involved in force production such as the hindlimb (biceps femoris muscle) or forelimb (pectoral muscle; Figures 2 and S2) muscles of the mice were studied. The levels and phosphorylation of proteins involved in glucose uptake, regulation of cellular energy level, protein synthesis, and cell survival were also analyzed. and with normalization on body weight (B). Gray column: control group before sham feeding (C); hollow column: control group after sham feeding (S); black column: AX fed group before feeding of astaxanthin-containing chow (C); red column: AX fed group after feeding of astaxanthin-containing chow (AX). All panels have the same arrangement as above; (C,D) Effects on CO 2 consumption without (C) and with normalization on body weight (D); (E) Normalized actions on food intake; (F) Changes in body weight gain. * denotes significant differences at p < 0.05.
Using the respiratory ratio (VCO 2 /VO 2 ), we calculated the calorific value (CV) using the equation (CV = 3.815 × 1.232 × RER), then total energy expenditure (TEE) was determined by multiplying CV and VO 2 . Subtracting resting/basal metabolic rate (RMR) from TEE we got the activity related energy expenditure (TEE activity ). Both versions of energy expenditure are plotted as a function of time ( Figure S1G,H, respectively).
In summary, mice kept on AX supplemented diet had increased food intake compared to the control group. In line with this, parameters related to in vivo metabolic activity did not change following the four weeks of special AX feeding.

Astaxanthin Feeding Influences the Activation of Signaling Molecules Affecting Skeletal Muscle Metabolism
Skeletal muscles are responsible for a significant proportion of metabolism of the whole organism; therefore, we aimed to investigate whether proteins regulating skeletal muscle metabolism are affected by the AX diet. AX was shown to accumulate in skeletal muscle [30]; therefore, the effects of long-term AX administration on representative muscles known to be involved in force production such as the hindlimb (biceps femoris muscle) or forelimb (pectoral muscle; Figures 2 and S2) muscles of the mice were studied. The levels and phosphorylation of proteins involved in glucose uptake, regulation of cellular energy level, protein synthesis, and cell survival were also analyzed.
Nanostring nSolver analysis revealed significant differences in fatty acid synthase (Fasn) and stearoyl-CoA desaturase (Scd1) gene expression (2.47-and 2.06-fold change following AX-treatment, respectively, Figure S3), while pyruvate dehydrogenase kinase 4 (Pdk4) and xanthine dehydrogenase (Xdh) gene expression levels were lower (0.54-fold change and 0.66-fold change, respectively) in AX samples compared to control. Quantile normalization and class comparison generated a heatmap ( Figure S3A) showing changes in gene expression between the two groups, but significant changes were also obvious following normalization of data for housekeeping genes ( Figure S3B).
To evaluate the aforementioned changes at protein expression level, additional experiments were conducted using protein samples from biceps femoris, pectoral, and EDL muscles from control and AX fed animals. Similar alterations of Pdk4 protein expression as seen on RNA level were observed in all investigated muscle types, which is significantly lower in AX-treated biceps femoris and EDL samples as compared to control (Figures 2A,B and S2C,D), respectively, while the Pdk4 protein expression showed only a slight decrease in the pectoral muscle of AX mice as compared with its control counterpart ( Figures 2B and S2B). Fasn protein expression was found to be significantly higher in AX-treated biceps femoris (Figures 2A and S2A); however, it was significantly lower in AX-treated EDL samples ( Figure S1C), while in pectoral muscles there was no significant difference between values from control and AX fed mice ( Figures 2B and S2B). We could not detect significant alteration of Scd1 protein level in muscle samples. Nanostring nSolver analysis revealed significant differences in fatty acid synthase (Fasn) and stearoyl-CoA desaturase (Scd1) gene expression (2.47-and 2.06-fold change following AX-treatment, respectively, Figure S3), while pyruvate dehydrogenase kinase 4 (Pdk4) and xanthine dehydrogenase (Xdh) gene expression levels were lower (0.54-fold change and 0.66-fold change, respectively) in AX samples compared to control. Quantile normalization and class comparison generated a heatmap ( Figure S3A) showing changes in gene expression between the two groups, but significant changes were also obvious following normalization of data for housekeeping genes ( Figure S3B).
To evaluate the aforementioned changes at protein expression level, additional experiments were conducted using protein samples from biceps femoris, pectoral, and EDL muscles from control and AX fed animals. Similar alterations of Pdk4 protein expression as seen on RNA level were observed in all investigated muscle types, which is significantly lower in AX-treated biceps femoris and EDL samples as compared to control (Figures 2A,B and S2C,D), respectively, while the Pdk4 protein expression showed only a slight decrease in the pectoral muscle of AX mice as compared with its control counterpart ( Figures 2B and S2B). Fasn protein expression was found to be significantly higher in AXtreated biceps femoris (Figures 2A and S2A); however, it was significantly lower in AXtreated EDL samples ( Figure S1C), while in pectoral muscles there was no significant difference between values from control and AX fed mice ( Figures 2B and S2B). We could not detect significant alteration of Scd1 protein level in muscle samples.
The levels and phosphorylation of proteins involved in glucose uptake, regulation of cellular energy level, protein synthesis, and cell survival were also analyzed. AX feeding increased mTOR phosphorylation (Ser2448) in biceps femoris and pectoral muscles (Figures 2A,B and S2A,B). Since the total amount of mTOR also increased, the mTOR(pSer2448)/mTOR ratio did not change significantly following AX treatment. AX feeding significantly increased pAS160/AS160 levels in both biceps femoris and pectoral muscle samples (Figures 2A,B and S2A,B). The expression of PGC-1α was slightly increased in biceps femoris and pectoral muscle samples following AX administration (Figures 2A,B and S2A,B). Akt2 is the skeletal muscle specific isoform of Akt, and the The levels and phosphorylation of proteins involved in glucose uptake, regulation of cellular energy level, protein synthesis, and cell survival were also analyzed. AX feeding increased mTOR phosphorylation (Ser2448) in biceps femoris and pectoral muscles (Figures 2A,B and S2A,B). Since the total amount of mTOR also increased, the mTOR(pSer2448)/mTOR ratio did not change significantly following AX treatment. AX feeding significantly increased pAS160/AS160 levels in both biceps femoris and pectoral muscle samples (Figures 2A,B and S2A,B). The expression of PGC-1α was slightly increased in biceps femoris and pectoral muscle samples following AX administration (Figures 2A,B and S2A,B). Akt2 is the skeletal muscle specific isoform of Akt, and the p(Ser474)Akt2/Akt2 ratio did not change significantly in the studied samples, as only a mild elevation could be observed in pectoral muscles (Figures 2A,B and S2A,B).
In summary, our findings regarding certain changes in enzymes of the skeletal muscles point towards higher levels of metabolism as well as anti-diabetic effects exerted by AX administration.

Hypothalamic Actions of Chronic Astaxanthin Feeding
AX fed animals had an increased food intake which raised the possibility that brain structures regulating food intake might be affected. As the hypothalamic arcuate nucleus has a key role in food intake, this nucleus became the subject of the next sets of experiments. Hypothalamic slices containing the arcuate nucleus were prepared and 17 neurons were patched from control and 15 from the AX fed mice.
At first, the general changes of the excitability were checked ( Figure 3A-E). There was no significant alteration of the input resistance (1065 ± 200 MΩ for control and 1163 ± 87 MΩ for fed mice, p = 0.36; Figure 3C). The maximal action potential firing frequency (measured as the frequency of the first two action potentials of the train elicited with 120 pA depolarization) was significantly greater (46 ± 8 Hz in control and 106 ± 18 Hz after feeding; p = 0.003; Figure 3D). The average firing rate elicited by increasing depolarizing steps also showed a tendency of increase with AX feeding (11.6 ± 2.5 vs. 24.3 ± 4.4 Hz at 50 pA depolarizing step, p = 0.01; 13.4 ± 4 vs. 32 ± 13 Hz at 100 pA depolarizing step, p = 0.0037; Figure 3E). ments. Hypothalamic slices containing the arcuate nucleus were prepared and 17 neurons were patched from control and 15 from the AX fed mice.
At first, the general changes of the excitability were checked ( Figure 3A-E). There was no significant alteration of the input resistance (1065 ± 200 MΩ for control and 1163 ± 87 MΩ for fed mice, p = 0.36; Figure 3C). The maximal action potential firing frequency (measured as the frequency of the first two action potentials of the train elicited with 120 pA depolarization) was significantly greater (46 ± 8 Hz in control and 106 ± 18 Hz after feeding; p = 0.003; Figure 3D). The average firing rate elicited by increasing depolarizing steps also showed a tendency of increase with AX feeding (11.6 ± 2.5 vs. 24.3 ± 4.4 Hz at 50 pA depolarizing step, p = 0.01; 13.4 ± 4 vs. 32 ± 13 Hz at 100 pA depolarizing step, p = 0.0037; Figure 3E). Secondly, changes of spontaneous excitatory and inhibitory postsynaptic potentials (EPSCs and IPSCs) were evaluated ( Figure 3F-I). We found that AX feeding did not alter the EPSC frequency and amplitude (the frequency was 0.95 ± 0.23 Hz in control and 1.09 ± 0.66 Hz after feeding, p = 0.41; the amplitude was 16.24 ± 2.02 pA in control and 15.74 ± 1.67 pA after feeding, p = 0.42; Figure 3H). On the contrary, the IPSC frequency was very low in the control group (0.0017 ± 0.0007 Hz) which became much greater in the AX fed Secondly, changes of spontaneous excitatory and inhibitory postsynaptic potentials (EPSCs and IPSCs) were evaluated ( Figure 3F-I). We found that AX feeding did not alter the EPSC frequency and amplitude (the frequency was 0.95 ± 0.23 Hz in control and 1.09 ± 0.66 Hz after feeding, p = 0.41; the amplitude was 16.24 ± 2.02 pA in control and 15.74 ± 1.67 pA after feeding, p = 0.42; Figure 3H). On the contrary, the IPSC frequency was very low in the control group (0.0017 ± 0.0007 Hz) which became much greater in the AX fed population (0.036 ± 0.014; p = 0.003). The IPSC amplitude did not change significantly (12.9 ± 2.4 pA in control and 9.53 ± 0.98 with AX feeding; p = 0.099; Figure 3I).
In summary, AX feeding led to increased excitability in neurons of the arcuate nucleus, together with an increased weight of inhibitory inputs.

Hypothalamic Effects of Acute Astaxanthin Application
In the next experiments, the acute responses to AX on different neuronal groups of the arcuate nucleus were evaluated. First, excitability and postsynaptic events of the POMC neurons (n = 8) were checked ( Figure 4A). The input resistance, the maximal and average firing rates did not show significant differences with AX application compared to control (input resistance: 515.5 ± 59.74 MΩ in control and 667.33 ± 112.2 MΩ with AX, p = 0.12; maximal firing rate: 42.68 ± 9.63 Hz in control and 42.85 ± 10.69 Hz with AX, p = 0.45; firing rate at 50 pA depolarizing step: 9.8 ± 2.25 Hz in control and 11.5 ± 2.46 Hz with AX, p = 0.31; firing rate at 100 pA depolarizing step: 11.8 ± 5.18 Hz in control and 10.25 ± 4.07 Hz with AX, p = 0.41; Figure 4B,C). Tonic currents developed during AX application were also investigated. At −60 mV holding potential, the spontaneous fluctuation of the holding current was −0.6 ± 1.35 pA, whereas AX application elicited −0.8 ± 1.19 pA tonic currents. Altogether the tonic current elicited by AX was not significantly different from the spontaneous fluctuation (p = 0.46; Figure 4D-F).
average firing rates did not show significant differences with AX application compared to control (input resistance: 515.5 ± 59.74 MΩ in control and 667.33 ± 112.2 MΩ with AX, p = 0.12; maximal firing rate: 42.68 ± 9.63 Hz in control and 42.85 ± 10.69 Hz with AX, p = 0.45; firing rate at 50 pA depolarizing step: 9.8 ± 2.25 Hz in control and 11.5 ± 2.46 Hz with AX, p = 0.31; firing rate at 100 pA depolarizing step: 11.8 ± 5.18 Hz in control and 10.25 ± 4.07 Hz with AX, p = 0.41; Figure 4B,C). Tonic currents developed during AX application were also investigated. At −60 mV holding potential, the spontaneous fluctuation of the holding current was −0.6 ± 1.35 pA, whereas AX application elicited -0.8 ± 1.19 pA tonic currents. Altogether the tonic current elicited by AX was not significantly different from the spontaneous fluctuation (p = 0.46; Figure 4D-F).  Similar to the feeding experiments, there was no change in EPSC frequency and amplitude following acute AX application (the frequency was 0.55 ± 0.21 Hz in control and 0.58 ± 0.27 with AX, p = 0.46; the amplitude was 13.07 ± 1.57 pA in control and 12.46 ± 1.05 pA with AX, p = 0.37, Figure 4H). The IPSC frequency was increased with AX application (from 0.001 ± 0.0006 to 0.086 ± 0.079 Hz, Figure 4G). In a single case, when no IPSCs were seen in control, IPSCs occurred in AX with a frequency of 0.402 Hz; whereas a milder increase was seen in 4 other cases. The rest of the neurons (n = 3) lacked IPSCs in all experimental conditions. Because of this fluctuation in the strength of this effect, the difference between the two datasets was not significant (p = 0.158). The IPSC amplitude did not change significantly (15.55 ± 6.45 pA in control and 10.45 ± 1.19 pA with AX, p = 0.19; Figure 4G).
In summary, acute application of AX causes a tendency of increase in the frequency of inhibitory event on POMC neurons. In a subset of neurons, this effect might be stronger.
Following these, the acute effects of AX on the local GABAergic neurons and synapses were investigated. For this, samples expressing GCaMP6f genetically encoded calcium indicator in GABAergic neurons (see Methods) were used. In total, 22 greater regions of interest (neuronal somata) produced calcium transients. Acute application of AX increased the calcium transient frequency or elicited calcium transients in 77.3% of the regions, it did not affect the activity in 9.1% and it decreased or blocked the calcium transient activity in the rest (13.6%; Figure 5A-C). Similar to this, smaller regions of interest (likely GABAergic axon terminals) produced similar response following AX administration. From 8 regions of interest, 3 decreased or ceased calcium transient activity, whereas 5 of them had increased calcium transient activity. The average calcium transient frequency was 2.42 ± 0.78 Hz which increased to 3.73 ± 0.75 Hz with AX; showing overall a 3.27-± 1.57-fold increase. However, due to the decrease of calcium transient frequency in a smaller population, the calcium transient frequency was not significantly greater following acute AX treatment (p = 0.11; Figure 5C). Spontaneous action potential firing rate of GABAergic neurons increased from 0.57 ± 0.13 to 1.12 ± 0.24 Hz (2.55 ± 0.67-fold increase, p = 0.036, n = 10, Figure 5D-F). Potential changes of excitatory inputs were also checked and no statistical difference was found in EPSC frequency and amplitude of GABAergic neurons (frequency in control: 0.19 ± 0.06 Hz, frequency in AX: 0.18 ± 0.05 Hz, p = 0.44; amplitude in control: 12.54 ± 1.45 pA, amplitude in AX: 13.12 ± 1.55 pA, p = 0.38, n = 8, Figure 5G,H). In 3 cases, the EPSC frequency had 1.62.3-fold increase, but the change in the EPSC amplitude was only 1.21-± 0.28-fold ( Figure 5H).
Based on the data above, we hypothesize that AX directly increases the excitability of a GABAergic neuronal subpopulation in the arcuate nucleus; however, the increase in excitatory drive on certain GABAergic neurons cannot be excluded.
In conclusion, suppression on POMC neuronal population and the stimulation on GABAergic neurons are in accordance with the findings on increased food intake.  Based on the data above, we hypothesize that AX directly increases the excitability of a GABAergic neuronal subpopulation in the arcuate nucleus; however, the increase in excitatory drive on certain GABAergic neurons cannot be excluded.
In conclusion, suppression on POMC neuronal population and the stimulation on GABAergic neurons are in accordance with the findings on increased food intake.

Effects of Astaxanthin on Action Potential Configuration in Canine Left Ventricular Myocytes
We were also interested to investigate whether AX diet could potentially exert arrhythmogenic actions thus we evaluated if cardiac excitability is affected in any way by AX supplementation.
Action potentials were recorded under steady-state conditions at 700 ms cycle length. After stabilization of action potential parameters in control (containing also 0.1% ethanol) the cells were exposed to 2.5 µM AX for 4-6 min. As presented in Figure 6, the duration somata in control and with AX (black, C: control, red, AX) in the neuronal groups where increase, no change or decrease was seen (from left to right, respectively). Increase was seen in 77.3%, no change was observed in 9.1% and decrease was detected in 13.6% of the neuronal somata; (D,E) spontaneous activity of GABAergic neurons in control (black) and with AX (red); (F) statistical comparison of the spontaneous and normalized firing rate under control conditions and with AX (black, C: control, red, AX); (G) statistical representation of EPSC frequency in control (black, C) and with astaxanthin (red, AX); (H) average frequency change (black square) and frequency changes of the individual cases (green: increase, red: decrease, yellow: no change). * p < 0.05, ** p < 0.01.

Effects of Astaxanthin on Action Potential Configuration in Canine Left Ventricular Myocytes
We were also interested to investigate whether AX diet could potentially exert arrhythmogenic actions thus we evaluated if cardiac excitability is affected in any way by AX supplementation.
Action potentials were recorded under steady-state conditions at 700 ms cycle length. After stabilization of action potential parameters in control (containing also 0.1% ethanol) the cells were exposed to 2.5 µM AX for 4-6 min. As presented in Figure 6, the duration of action potentials was significantly reduced by AX both at 50% and 90% levels of repolarization (APD 50 and APD 90 , respectively, Figure 6A,D,F). AX also significantly decreased the maximal rate of depolarization (V + max) and the mid-plateau potential (measured at the time of 50% repolarization, Figure 6H,I). Other parameters, such as the resting membrane potential (−84.3 ± 0.9 vs. −83.1 ± 2.1 mV, Figure 6C), action potential amplitude (118.8 ± 2.4 vs. 113.5 ± 4.5 mV, Figure 6E), and maximal rate of repolarization (−1.4 ± 0.1 vs. −1.4 ± 0.1 V/s, Figure 6J) were not altered significantly by AX. of action potentials was significantly reduced by AX both at 50% and 90% levels of repolarization (APD50 and APD90, respectively, Figure 6A,D,F). AX also significantly decreased the maximal rate of depolarization (V + max) and the mid-plateau potential (measured at the time of 50% repolarization, Figure 6H,I). Other parameters, such as the resting membrane potential (−84.3 ± 0.9 vs. −83.1 ± 2.1 mV, Figure 6C), action potential amplitude (118.8 ± 2.4 vs. 113.5 ± 4.5 mV, Figure 6E), and maximal rate of repolarization (−1.4 ± 0.1 vs. −1.4 ± 0.1 V/s, Figure 6J) were not altered significantly by AX. In conclusion, acute AX administration does not seem to alter significantly cardiac excitability thus no serious risk of arrhythmias can be predicted.

Discussion and Conclusions
In this work, AX supplementation did not change markedly the metabolic parameters measured in vivo, however it facilitated food intake. As a possible reason for changes in food intake, inhibitory inputs of hypothalamic POMC neurons were strengthened. In parallel with these, carbohydrate signaling of skeletal muscle was altered which potentially increased metabolism in muscle and caused anti-diabetic effects. Kinetics of the cardiac action potentials were slightly altered but this change did not predict a greater risk for arrhythmias.

In Vivo Effects of Astaxanthin
We propose that AX supplemented feeding could affect the glucose metabolism and fatty acid biosynthesis in mouse skeletal muscles. The cumulative food intake increased significantly during 4 weeks of treatment in the AX group ( Figure 1E). The cumulative O2usage and cumulative CO2-production were not altered significantly following 4 weeks of AX supplementation ( Figure 1A,C). On the other hand, the XY-movements and total activity were significantly lower in each group following 4 weeks of normal or special AX feeding. These findings could explain why AX administration would not be enough to In conclusion, acute AX administration does not seem to alter significantly cardiac excitability thus no serious risk of arrhythmias can be predicted.

Discussion and Conclusions
In this work, AX supplementation did not change markedly the metabolic parameters measured in vivo, however it facilitated food intake. As a possible reason for changes in food intake, inhibitory inputs of hypothalamic POMC neurons were strengthened. In parallel with these, carbohydrate signaling of skeletal muscle was altered which potentially increased metabolism in muscle and caused anti-diabetic effects. Kinetics of the cardiac action potentials were slightly altered but this change did not predict a greater risk for arrhythmias.

In Vivo Effects of Astaxanthin
We propose that AX supplemented feeding could affect the glucose metabolism and fatty acid biosynthesis in mouse skeletal muscles. The cumulative food intake increased significantly during 4 weeks of treatment in the AX group ( Figure 1E). The cumulative O 2usage and cumulative CO 2 -production were not altered significantly following 4 weeks of AX supplementation ( Figure 1A,C). On the other hand, the XY-movements and total activity were significantly lower in each group following 4 weeks of normal or special AX feeding. These findings could explain why AX administration would not be enough to counteract the effects of weight gain by itself ( Figure 1G) due to increased food consumption. We thus propose that AX administration should be combined with adequate diet regimen and exercise to maintain a healthy body mass index.

Effects of Astaxanthin on Skeletal Muscle Metabolism
Our data suggest that AX exerts new signaling effects which can greatly influence skeletal muscle metabolism.
We detected significantly altered mRNA, and in some cases (see below) protein expression levels of Fasn, Pdk4, Scd1, and Xdh in AX supplemented muscle samples compared to the control group. Studies have shown that the increase in muscle Pdk4 activity in starvation and streptozotocin-induced diabetes were due to a selective upregulation of Pdk4 expression [31], which may largely be due to insulin deficiency rather than to increases in circulating free fatty acids (FFA) [32][33][34]. Data also suggest that increased Pdk4 activity in skeletal muscle might contribute to the development of insulin resistance by suppressing glucose oxidation [31]. Insulin stimulation of PI3K and/or Akt is often impaired in insulin resistant states [35,36], and this would decrease insulin's ability to regulate FOXO1 activity [37] and Pdk4 expression. Thus, increased Pdk4 expression, which would inhibit glucose oxidation, may be an important adaptive mechanism for glucose conservation [38]. Pdk4 phosphorylates and inhibits the PDH complex that catalyzes the conversion of pyruvate to acetyl-CoA. In our case, lower Pdk4 level and thereby increased PDH activity likely increased the generation of acetyl-CoA. This further elevated the synthesis of malonyl-CoA, the first molecule of fatty acid synthesis, causing increased Fasn4 production. Activation of PDH by downregulation of Pdk4 supports glucose catabolism instead of fatty acid utilization. Intracellular malonyl-CoA is an important factor in the regulation of fatty acids (FA); in healthy muscle, malonyl-CoA levels are associated with reciprocal changes in FA oxidation. Altogether, our results suggest increased glucose uptake which provides the possibility of elevated protein synthesis in skeletal muscles. Nevertheless, we recorded cumulative O 2 usage, CO 2 production, VO 2 , and VCO 2 that were higher in AX animals, possibly because of their increased body weight. This explains why the normalized parameters were found to be significantly lower following AX supplemented feeding.
AS160 is a Rab GAP that regulates glucose uptake of skeletal muscle by controlling the activity of Rab GTPases. As a consequence, vesicular transport of GLUT4 from the cytosol to the plasma membrane increases which leads to increased glucose uptake. The increased phosphorylation of AS160 (pAS160) is an essential signal for the glucose uptake of skeletal muscle and adipose tissue. Earlier studies described that AX treatment increases glucose uptake in L6 myoblasts [19] or in high fat and high fructose diet-fed mice [20]. In our work, AX feeding significantly increased pAS160/AS160 levels in both biceps femoris and pectoralis muscle samples (Figures 2A,B and S2). The increased phosphorylation of AS160 can explain the beneficial effects of AX to improve insulin sensitivity. In the case of insulin resistance and type-2 diabetes mellitus the cellular amount of GLUT4 is decreased [39] and its translocation is impaired [40]; therefore, the improvement of GLUT4 translocation decreases blood glucose level. The increased pAS160/AS160 ratio following AX feeding presumably increases intracellular glucose levels and, consequently energy levels, allowing cells to improve protein synthesis and muscle mass gain. This idea is further supported by an increase in mTOR phosphorylation in the AX-fed group, since mTOR stimulates protein synthesis and inhibits autophagy [41,42]. Here, we found that AX feeding increased mTOR phosphorylation (Ser2448) in biceps femoris and pectoralis muscles (Figures 2A,B and S2). Since the total amount of mTOR also increased, the mTOR(pSer2448)/mTOR ratio did not change significantly following AX treatment.
PGC-1α is a transcriptional coactivator important in energy metabolism and a master regulator of mitochondrial biogenesis. Moreover, PGC-1α also increases GLUT4 levels and has multiple roles in the pathogenesis of type-2 diabetes mellitus [43,44]. In our experiments, the expression of PGC-1α slightly increased in biceps femoris and pectoralis muscle samples following AX administration (Figures 2A,B and S2) which is in accordance with a previous work [12] where PGC-1α was significantly elevated in skeletal muscle samples following AX intake in mice.
Although increased phosphorylation of Akt was earlier described in L6 muscle cells following AX administration [19], the p(Ser474)Akt2/Akt2 ratio did not change in our study (Figures 2A,B and S2).

Effects of Astaxanthin on Hypothalamic Neuronal Activity
The hypothalamic arcuate nucleus has a central role in food intake. Its two major neuronal types have distinct roles in appetite regulation: the anorexigenic POMC neurons decrease, whereas the orexigenic NPY-and AgRP-expressing neurons stimulate food intake [26][27][28]. Decreased activity of POMC cells is associated with obesity [26,29], whereas selective stimulation of them leads to weight loss [45].
GABAergic inputs to POMC neurons are capable of modulating them according to the actual energetic status of the organism [46]. POMC cells receive GABAergic inhibitory inputs from the dorsomedial hypothalamus (DMH) and the orexigenic hypothalamic AgRP neurons [26,29,47,48]. The frequency of spontaneous IPSCs onto POMC neurons increases during caloric deficits [26].
Glucose and fatty acid metabolism can affect cells of the arcuate nucleus by defining functional subgroups. There are glucose-excited and glucose-inhibited neurons reflecting changes of extracellular glucose levels in the normal range. Direct interaction was shown between glucose metabolism and fatty acid detection in regulation of neuronal activity in the arcuate nucleus. There are both oleic acid (OA) excited and oleic acid inhibited neurons, which are sensing glucose as well [49][50][51][52].
Mendoza et al. [53] investigated the effect of krill oil on restraint stress (RS) causing depressive-like behavior, memory deficiency and anxiety. Krill oil with high AX content has been shown to decrease depressive-like behavior and oxidative stress. Applying krill oil prevented appearance of depressive-like behavior and cognitive impairment by RS.
In the present work, we surprisingly found that, in contrast with oleic acid, AX did not elicit tonic changes of excitability. However, resembling conditions in hunger, an increase of sIPSC frequency on POMC neurons was seen. This increase was due to pleiotropic actions on GABAergic neurons, as the spontaneous firing rate was increased, probably partially caused by the strengthening of excitatory inputs in some cases. As inhibition of POMC neurons increases feeding, the increase of GABAergic activity might contribute to the increased food consumption seen with chronic AX supplementation. Although coronal slices contained the main sources of GABAergic inputs of the POMC neurons, the arcuate nucleus and the DMH, actions on the IPSCs were probably underestimated, as certain synaptic connections were lost in brain slices.

Effects of Astaxanthin on Cardiac Excitability
According to our knowledge cellular electrophysiological effects of AX in mammalian cardiac tissues were not reported yet. In present study, we used canine ventricular myocytes as their electrical properties greatly resemble those of the human myocardium [54,55]. Furthermore, canine heart is believed to be a good model to study the cardioprotective effects of AX [56]. Acute AX treatment shortened the action potential, depressed the plateau potential and reduced depolarization velocity ( Figure 6A,I,H). These changes are congruent with a mild inhibition of inward currents (such as the L-type Ca 2+ and Na + currents) by AX. A reduction in Ca 2+ entry may also contribute to the well documented cardioprotective effect of AX [57], presently attributed to decreasing the consequences of oxidative stress by supporting the function of the mitochondria [15,58,59]. Since the resting potential and the maximal rate of repolarization remained unchanged, AX seems to leave the inward rectifier K + current unaffected ( Figure 6C,J). However, further detailed studies are required to elucidate the exact molecular mechanisms of the cardiac electrophysiological effects of AX.
In conclusion, we propose that AX exerts complex effects on whole body metabolism (Figure 7). It affects food intake via hypothalamic regulatory centers of energy homeostasis, as well as via increased metabolism and anti-diabetic actions by direct effects on the target organs of mice; without presenting serious risks for cardiac arrhythmias on a canine model. Our results support the idea that AX, this widely used nutraceutical, is a potent candidate for treatment of diseases of energy homeostasis; however, one must acknowledge that solely its administration will not replace a healthy diet and lifestyle but rather will be best achieved in conjunction with them.
physiological effects of AX.
In conclusion, we propose that AX exerts complex effects on whole body metabolism (Figure 7). It affects food intake via hypothalamic regulatory centers of energy homeostasis, as well as via increased metabolism and anti-diabetic actions by direct effects on the target organs of mice; without presenting serious risks for cardiac arrhythmias on a canine model. Our results support the idea that AX, this widely used nutraceutical, is a potent candidate for treatment of diseases of energy homeostasis; however, one must acknowledge that solely its administration will not replace a healthy diet and lifestyle but rather will be best achieved in conjunction with them. Figure 7. Proposed mode of action of AX in mice. Summary of our findings on the responses by AX on skeletal muscle metabolism, cardiac excitability and hypothalamic neuronal activity that could lead potentially to weight gain. AX facilitates the increase in metabolism and exerts anti-diabetic actions on skeletal muscle, promotes food intake via actions on the hypothalamus, and exerts minor changes on cardiac excitability.

Animals
Animal experiments were conducted in accordance with the appropriate national and international (EU Directive 2010/63/EU for animal experiments) institutional guidelines and laws on the care of research animals. Experimental protocols were approved by the Committee of Animal Research of the University of Debrecen (3-1/2019/DEMÁB).
Young adult (3-months-old) wild-type mice C57BL6 (n = 16) were used for chronic, 4-week-long AX feeding experiments (8 were fed with AX supplemented chow and 8 were fed normal rodent chow). The special chow was prepared with the addition of 4 g/kg of AstaReal A1010 (dissolved in 100% ethanol) to the standard rodent pellet (protein 20%, Figure 7. Proposed mode of action of AX in mice. Summary of our findings on the responses by AX on skeletal muscle metabolism, cardiac excitability and hypothalamic neuronal activity that could lead potentially to weight gain. AX facilitates the increase in metabolism and exerts anti-diabetic actions on skeletal muscle, promotes food intake via actions on the hypothalamus, and exerts minor changes on cardiac excitability.

Animals
Animal experiments were conducted in accordance with the appropriate national and international (EU Directive 2010/63/EU for animal experiments) institutional guidelines and laws on the care of research animals. Experimental protocols were approved by the Committee of Animal Research of the University of Debrecen (3-1/2019/DEMÁB).
Young adult (3-months-old) wild-type mice C57BL6 (n = 16) were used for chronic, 4-week-long AX feeding experiments (8 were fed with AX supplemented chow and 8 were fed normal rodent chow). The special chow was prepared with the addition of 4 g/kg of AstaReal A1010 (dissolved in 100% ethanol) to the standard rodent pellet (protein 20%, carbohydrates 70%, fats 4%, fibers 5%, vitamins, micro-and macronutrients) for a final concentration of 0.02% AX. This concentration was chosen according to the literature [13,15]. The mice had ad libitum access to water and food intake. Room illumination was set automatically to cycles of 12-h dark and 12-h light.
For acute experiments, mice expressing the tdTomato fluorescent protein in a proopiomelanocortin (POMC)-or glutamate decarboxylase type 2 (GAD2)-dependent way (n = 8 for both groups), as well as mice expressing GCaMP6f genetically encoded calcium indicator in a type 2 vesicular gamma-amino-butyric acid transporter (VGAT2) dependent way were used (n = 3) from both sexes. Homozygous floxed-stop tdTomato

Metabolic Cage Experiments
A Comprehensive Lab Animal Monitoring System (CLAMS) was used to monitor the metabolism of 8 control and 8 AX-treated mice. Three-month-old animals were selected for the experiments and were divided into 4 groups. As the monitoring system could measure 8 animals at the same time, 4-4 mice were measured for control and AX group, then the remaining 4-4 animals were put into the special cages. During 48 h of continuous monitoring, several parameters (food and water intake, calorimetry data, activity of the animals, and sleeping time) were followed where total or accelerated (cumulative) data were given for the whole measuring period or for 12 h of dark and light daily periods.
Animal activity was recorded with an array of infrared photo beams that surround the cage. When the animal moved, the beams were interrupted, generating one count. Since the beams were arranged in a grid pattern, the XY position of the animal could be continuously recorded (X amb ). When equipped with the Z axis sensor, total movements could be determined (X total ). Bouts of inactivity of certain duration were scored in an event file as sleeping events.
The system collected calorimetry parameters: VO 2 , VCO 2 , RER, and heat production. The calculation of oxygen consumption (VO 2 ) and carbon dioxide production (VCO 2 ) values required the use of both the input (Vi) and output (Vo) flows to the chamber. The respiratory exchange ratio (RER) can be calculated from either set of consumption and production rates (RER=VCO 2 /VO 2 ). Calorific value (CV) was calculated from RER using the following equation: CV = 3.815 × 1.232 × RER. Total energy expenditure (TEE) was calculated by multiplying CV and VO 2 . As this parameter contain resting/basal metabolic rate and activity related energy expenditure, resting metabolic rate was determined by averaging the ten minima values of energy expenditure within the 48-h measurement. RMR was subtracted from TEE giving the TEE activity values.

Metabolic Pathways Panel
Functional annotations for different pathways and processes were assigned to the genes in the nCounter Metabolic Pathways Panel (Nanostring, Fairview, WA, USA). The pathways and processes that are included in this panel provide a comprehensive view of cell metabolism. Exact genes regarding the different metabolic pathways can be found at the website of Nanostring company.
Total RNA samples were prepared from m. extensor digitorum longus (EDL) of 6 control and 6 AX-treated mice following 4 weeks of special feeding. The samples were subjected to RNA isolation using Trizol reagent (Sigma-Aldrich, St. Louis, MO, USA). The concentration of the samples was determined by the Nanodrop2000 spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA). Samples were loaded into the specific metabolic panel and the appropriate reaction was carried out. Data were first analyzed using the nSolver program, where all data from the metabolic program measurement were normalized to 12 different housekeeping genes and the threshold suggested by Nanostring was determined from these results. Significant differences between control and AX-treated samples were determined by giving the fold change ratio of the appropriate genes. BRB array tool analysis was used to further improve the quality of the measurement and to ensure the assessment of significant changes of certain genes.
After decapitation of the animal and removal of the brain, 200-µm-thick coronal slices were prepared from the area including the hypothalamus in ice-cold low Na aCSF with a Microm HM 650V vibratome (Microm International GmbH, Walldorf, Germany). Prior to recording, the slices were incubated in normal aCSF for 60 min at 37 • C.

Isolation of Canine Ventricular Myocytes
Single myocytes were obtained by enzymatic dispersion using the segment perfusion technique. Briefly, the heart was quickly removed and washed in a cold Tyrode's solution. Left anterior descending coronary artery was cannulated, then a wedge-shaped section of the ventricular wall supplied by the artery was dissected and perfused with a nominally Ca 2+ -free Joklik solution (Minimum Essential Medium Eagle, Joklik Modification, Sigma-Aldrich Co., St. Louis, MO, USA, product no. M0518) for 5 min. This was followed by perfusion with Joklik solution supplemented with 1 mg/mL collagenase (Type II, Worthington Biochemical Co., Lakewood, NJ, USA) and 0.2% bovine serum albumin (Fraction V., Sigma) containing 50 µM Ca 2+ for 30 min. After this, normal external Ca 2+ concentration was gradually restored, and cells were kept in Minimum Essential Medium Eagle (Sigma-Aldrich Co., product no. M0643) until use.
For recording action potential trains, a current clamp protocol with 1-s-long depolarizing steps was employed from −30 to +120 pA with 10 pA increments. The resting membrane potential was set to −60 mV. Recordings of spontaneous firing rates was done in current clamp mode. The neurons were kept on their own resting membrane potential and no current injection was administered. Fifty-second-long traces were evaluated with each neuron and condition.
For tonic currents and spontaneous EPSCs and IPSCs, gap-free voltage-clamp traces were recorded at a holding potential of −60 mV before and after drug application (10 min in each condition). Tonic currents were assessed by making histograms of the recorded current values from the last minute of the trace; and the current values at the histogram peaks were considered as the amplitude of the tonic current. Spontaneous changes of the holding current were calculated as the difference between the first and the last minute of the control recording. At the end of the experiment, slices were continuously perfused with 10 µM of 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline-2,3-dione (NBQX), 50 µM if D-2-amino-5-phosphonopentanoate (D-AP5), 1 µM of strychnine, and 10 µM of bicuculline (Tocris Cookson Ltd., Bristol, UK).
Cardiac action potentials were recorded at 37 • C, maintained by an electronic temperature controller (Cell MicroControls, Norfolk, VA, USA). The rod-shaped viable cells showing clear striation were sedimented in a plexiglass chamber of 1-mL volume allowing continuous superfusion (at a rate of 2 mL/min) with Tyrode's solution. The Tyrode solution contained (in mM): NaCl, 121; KCl, 4; MgCl 2 , 1; CaCl 2 , 1.3; HEPES, 10; glucose, 10; NaHCO 3 , 25; at pH = 7.3. Membrane voltage was recorded using 3 M of KCl filled sharp glass microelectrodes having tip resistance between 20 and 40 MΩ. These electrodes were connected to the input of an Axoclamp 2B, Multiclamp 700A or 700B amplifiers (Molecular Devices, Sunnyvale, CA, USA). The cells were paced through the recording electrode at steady cycle length of 0.7 s using 1-2 ms wide rectangular current pulses having amplitudes of 120% diastolic threshold. Action potentials were digitized (at 50 kHz using Digidata 1322A or 1440A A/D card, Molecular Devices, Sunnyvale, CA, USA) and stored for later analysis. Cells were exposed to 2.5 µM of AX for 4-6 min (dissolved in ethanol yielding a final ethanol concentration of 0.1%). Control solution also contained this concentration of ethanol.

Calcium Imaging
Calcium imaging experiments were performed on slices from VGAT2-GCaMP6 mice. Slices were prepared similarly as for electrophysiology experiments. A Zeiss Axioscope microscope (Carl Zeiss AG) equipped with a fluorescent imaging system (Till Photonics GmbH, Gräfeling, Germany) containing a xenon bulb-based Polychrome V light source, a CCD camera (SensiCam, PCO AG, Kelheim, Germany), an imaging control unit (ICU), and the Till Vision software (version 4.0.1.3) were used. The fluorescent filter set contained an emission filter (LP 515, Till Photonics) and a dichroic mirror (Omega XF2031 505DRLPXR; Omega Drive, Brattleboro, VT, USA). Frames with 344 × 260-pixel resolution were taken with a frame rate of 10 Hz.

Statistics
Results are expressed as mean ± SEM values. GraphPad Prism 7.0 (GraphPad Software Inc., San Diego, CA, USA) was used for graphing and statistical analyses. Statistical significance of differences was evaluated using Student's t-test. Differences were considered significant when p was less than 0.05.


Nanostructured Silicon Enabled HR-MS for the Label-Free Detection of Biomarkers in Colorectal Cancer Plasma Small Extracellular Vesicles

: Despite improvements in treatment options for advanced colorectal cancer (CRC), survival outcomes are still best for patients with non-metastasised disease. Diagnostic tools to identify blood-based biomarkers and assist in CRC subtype classiﬁcation could afford a means to track CRC progression and treatment response. Cancer cell-derived small extracellular vesicles (EVs) circulating in blood carry an elevated cargo of lipids and proteins that could be used as a signature of tumour suppressor/promoting events or stages leading up to and including metastasis. Here, we used pre-characterised biobanked plasma samples from surgical units, typically with a low volume (~100 µ L), to generate and discover signatures of CRC-derived EVs. We employed nanostructured porous silicon (pSi) surface assisted-laser desorption/ionisation (SALDI) coupled with high-resolution mass spectrometry (HR-MS), to allow sensitive detection of low abundant analytes in plasma EVs. When applied to CRC samples, SALDI-HR-MS enabled the detection of the peptide mass ﬁngerprint of cancer suppressor proteins, including serine/threonine phosphatases and activating-transcription factor 3. SALDI-HR-MS also allowed the detection of a spectrum of glycerophospholipids and sphingolipid signatures in metastatic CRC. We observed that lithium chloride enhanced detection sensitivity to elucidate the structure of low abundant lipids in plasma EVs. pSi SALDI can be used as an effective system for label-free and high throughput analysis of low-volume patient samples, allowing rapid and sensitive analysis for CRC classiﬁcation.

Introduction
Blood-circulating small extracellular vesicles (EVs) offer a potential biochemical signature in exploring the cross-talk between cancerous and healthy cells. EVs are nano-sized vesicles ranging between 30 and 150 nm, which contain bioactive compounds such as nucleic acids (DNA, microRNA and mRNA), proteins (including chemokines), cytokines and growth factors enclosed in a lipid bilayer. Compared to healthy proliferating cells, colorectal cancer (CRC) cells often release excess EVs, carrying tumour derived molecules [1]. EVs are involved in angiogenesis (formation of new blood vessels) in cancer progression by transporting various pro-angiogenic molecules such as matrix metalloproteinases, vascular endothelial growth factors and microRNAs [2]. Additionally, exosomal lipid rafts are bound to integral proteins, surrounded by membrane lipids, and these lipids are major contributors to protein sorting, cell-cell communication and cancer cell recognition in CRC progression [3].
The nature of EVs found in the blood is directly related to molecular changes in CRC cells, rendering EVs an effective probe for longitudinal clinical follow-up in metastatic CRC prognosis [4]. Evidence has shown that several tumour relevant proteins can be detected on the surface of the circulating EVs that may facilitate blood-based rapid CRC diagnosis (liquid biopsy) [5,6]. Specifically, EVs-receptor proteins are of importance to differentiate stages of malignant tumours and progression towards liver metastasis. Belove et al. identified a subset of human leukocyte antigen complexes and 10 receptor proteins, including CD5, CD31, CD44, which were differentially expressed in EVs derived from CRC cell lines (LIM1215 and MEC1); importantly, these proteins were not detected in healthy serum samples [7]. Studies using mRNA and protein expression profiling methods have illustrated that CRC cell-derived EVs contain many mRNAs or proteins associated with oncogenes or metastasis-related genes [8][9][10], suggesting that EVs might be connected to the liver metastasis of CRC. However, no direct evidence for EVs involved in CRC metastasis has previously been provided. Therefore, this study is designed to discover possible signatures in the promotion CRC to liver metastasis.
CRC-derived EVs found in biological fluids are enriched in lipids such as cholesterol (CL) (55%), sphingomyelin (SM) (28%), hexosyl-ceramide (5.5%), phosphatidylserine (PS) (7%), phosphatidylcholine (PC) (2%), phosphatidylinositol (PI) (1%), and phosphatidylethanolamine (PE) (0.6%) [11]. A mass spectrometry-based lipidomics analysis conducted by Lydic et al. identified more than 520 lipid species upregulated in EVs secreted by the CRC cell line LIM1215. Among them, plasmalogen, ceramide, sphingomyelin subspecies and glycerophospholipids, such as phosphatidylcholine and phosphatidylserine, were enriched in LIM1215 derived EVs [12]. Currently, most CRC-relevant proteins and lipid-based biomarkers in blood-circulating EVs are yet to be comprehensively characterised. A major challenge in detecting CRC signatures in blood is the dominance of major proteins, such as albumin and platelet factors, which necessitates selective fractionation [13]. However, fraction collecting methodologies that are mass spectrometry compatible are not readily reproducible, in regard to major protein depletion, or sufficiently selective [14]. In addition, once purified, no definitive biological methods are specific enough to differentiate exosomal biomarkers for metastatic CRC diagnosis from normal endogenous EVs [15]. Fit-for-purpose diagnostic techniques for sensitive and selective analysis of CRC derived EVs are urgently required.
Advances in mass spectrometry and iterative improvements in multi-omics analysis have enabled comprehensive molecular analysis of multiple biomarkers to detect early signs of disease. Matrix-assisted laser desorption ionisation is a widely used analytical approach for sensitive detection (down to femtomolar) of biomolecules such as lipids, proteins or peptides with the aid of a co-crystallising chemical matrix (e.g., α-cyano-4hydroxycinnamic acid). MALDI-MS offers excellent sensitivity and can be applied rapidly to 'phenotype' low sample volumes. However, when looking at the combination of lipids and peptides/proteins, the addition of the co-crystallising matrix can mask the detection of target groups (lipids) and short sequence peptides from tryptic digestion. To circumvent this issue, nanostructured surfaces have been created that take on the role of the matrix, absorbing and diffusing laser energy for photoionisation.
Surface-assisted laser desorption/ionisation (SALDI) is emerging as a promising tool for protein and small-molecule analysis [16]. pSi SALDI substrates such as nanostructureinitiator mass spectrometry (NIMS) and desorption/ionisation on silicon (DIOS) comprise distinct surface chemistry, pore size and depth, enabling accurate identification of the spectrum of molecules that differ in size. Fourier-transform ion cyclotron resonance-high resolution-mass spectrometry (HRMS) enabled SALDI substrates offer high mass spectral performance for molecular analysis [16,17]. Additionally, the performance of SALDI can be enhanced by implementing lithium adduct materials added to plasma samples. Lithiatedlipids reduce spectral complexity, specifically when detecting low abundant lipids in samples with limited sample volume.
This study used SALDI-HR-MS to detect CRC-associated proteins (using a bottom-up analysis), and lithiated lipid subsets in EVs, isolated from~100 µL banked CRC plasma. Two pSi SALDI substrates: (a) NIMS using pSi substrates with an average pore size of 100 nm (in diameter) and 3.5 µm in-depth (i.e., thickness), and (b) DIOS using pSi substrates with a pore size of 120 nm and 450 nm in-depth, were employed to detect proteins and lipids, respectively, in a low volume of patient sample. The schematic representation shows the workflow of the method used to identify disease-relevant signatures in plasma EVs (Supplementary Materials, Figure S1). SALDI-HR-MS identified peptide ions to match against known tumour suppressor or promoting proteins, such as serine/threonine phosphatases (PP2A) and activating transcription factor-3 (ATF3), implicated in metastatic CRC. Lithium-consolidated analysis revealed that a range of exosomal lipid markers, including phosphatidylcholine, ceramide and phosphatidylinositol subsets, may be combined with EVs protein markers to derive a staged signature of CRC. In conclusion, SALDI-HR-MS represents a promising analytical tool for rapidly diagnosing metastatic CRC using low volumes (~100 µL) of banked plasma.

Materials and Methods
Blood plasma samples were received from The Queen Elizabeth Hospital (TQEH), South Australia, with the approval of the TQEH Human Research Ethics Committee (HREC) and the Monash University HREC. We have categorised sample groups into (i) cancer free individual (CFI) and healthy participants, (ii) CRC-contain CRC samples stage I to IV (stage IV CRC metastasis to any organ except liver) and (iii) CLM-colorectal cancer liver metastasis. A total of 27 samples were used for the analysis, including 11 CFI samples, 10 CRC samples and 6 CLM samples. All samples were de-identified and received in a closed container maintained at −80 • C. The plasma samples were thawed to 20 • C before performing EVs isolation.

Isolation of Circulating EVs from Plasma Samples
According to the manufacturer's recommendation, the plasma EVs were isolated using the total exosome isolation kit (Invitrogen 4478359). The EVs were isolated from 100 µL of blood plasma by adding 50 µL of exosome isolation reagents and vortexed for 2 min. The mixture was incubated at 4 • C overnight. Samples were then centrifuged at 10,000× g for 1 h at 4 • C. After centrifugation, the supernatant was discarded, and the pellets containing EVs were resuspended in 200 µL aliquots of phosphate-buffered saline (PBS) for protein and lipid analysis and stored at −20 • C.

Transmission Electron Microscopy Phosphotungstic Acid (TEM PTA) Negative Staining Protocol
The EVs morphology was characterised by TEM PTA negative staining. Initially, the total EVs protein concentration was measured using a Pierce™ Rapid Gold BCA Protein Assay Kit. Bovine serum albumin (20 µL solution, concentration from 20 to 2000 µg/mL) was used for calibration-the total protein concentration by measuring absorbance at 480 nm wavelength. The CRC proteins were diluted to 20 µg/mL in PBS for TEM analysis. Copper grids of 400-mesh coated with carbon film (EMSFCFTH400H-CU ProSciTech, Qld, Australia) were glow discharge treated in nitrogen using a Pelco easiGlow (Ted Pella Inc., Redding, CA, USA) to render the grids hydrophilic. A 3 µL aliquot of the sample was pipetted onto each grid, allowed to remain for 10 min and the excess fluid blotted away, the sample was fixed with 3% glutaraldehyde in Sorenson's phosphate buffer, pH 7.2 (# 16539-45 ProSciTech, Qld, Australia) for 2 min, the excess blotted and replaced with 2 washes of Sorenson's buffer (# ASOR68C ProSciTech, Kirwan, QLD, Australia) at working dilution, blotted, then stained with 2% aqueous phosphotungstic acid pH 6.9 for 1 min, excess fluid was blotted and air-dried. The samples were examined using a Tecnai 12 Transmission Electron Microscope (FEI, Eindhoven, The Netherlands) at an operating voltage of 120 kV. Images were recorded using an FEI Eagle 4k × 4k CCD camera and AnalySIS v3.2 camera control software (Olympus, New South Wales, Australia).

Nanoparticle Tracking (NTA) for EVs Size Characterisation
The size distribution of isolated EVs was characterised using NanoSight NS300 (Malvern Panalytical, New South Wales, Australia. A 10 µL aliquot of EVs sample was mixed with 990 µL filtered PBS solution (0.22 µm filter) and diluted 1:1000 ratio for improved characterisation. The analysis was performed 5 times (60 s each) with 25 frames per s. For NTA analysis, the detection threshold was set at 2, camera level 8, and a media dilution of 1:1000, and the same settings were used throughout all experiments.

Extraction of Lipids and Proteins from EVs
The Folch method was used to extract exosomal lipids. Briefly, 100 µL of each aliquoted sample was lysed using a probe sonicator for 3 × 10 s. Two mL of a mixture of methanol: chloroform (1:2 v/v) was added directly to the 100 µL of the lysed samples. The homogenous mixture was vortexed and incubated for 20 min. Following mixing, a 0.9% NaCl solution was added to each sample. The samples were then centrifuged for 500× g for 15 min. After phase separation, the lower phase containing lipids in chloroform was transferred to a new amber tube and allowed to dry under N 2 gas. The dried lipid extracts were resuspended in chloroform (5 mg/mL of final concentration) and stored at −80 • C for further analysis.
Albumin is the most abundant protein in blood plasma, which often interferes with untargeted protein analysis, and it is hence crucial to perform an albumin reduction step [18]. Briefly, 100 µL of each EVs sample was lysed using a probe sonicator, 3 × 10 s, to extract the proteins encapsulated by the exosomal lipid bilayers. One hundred µL of the lysed samples were incubated with 1% (by weight) of trichloroacetic acid (Merck Pty. Ltd., Bayswater, Australia) in isopropanol at a ratio of 1:10 (sample to organic solvent), which has been measured to remove~95% of human serum albumin effectively. After initial albumin removal, the samples were vortexed and centrifuged at 1500× g at 4 • C for 5 min. Following centrifugation, the supernatant was discarded, and the pellets were washed with 200 µL of HPLC grade methanol (Sigma-Aldrich, St. Louis, MO, USA). Following this, the samples were vortexed and centrifuged at 600× g at 4 • C for 3 min. The supernatant was removed, and the pellet was dried completely by incubation at 95 • C for 30 s. The pellets were resuspended in 100 µL of 100 mM Tris-HCl, pH 8.1, and incubated at 95 • C for 10 min to denature the remaining intact proteins. Alkylating and reducing agents (10 mM iodoacetamide and 40 mM tris(2-carboxyethyl)phosphine hydrochloride), prepared in Tris-HCl, pH 8.1 buffer, were added for 10 min at 95 • C in order to reduce disulfide bonds and alkylate the resulting thiols. Before performing tryptic digestion, the total protein concentration was measured using the Pierce™ Rapid Gold BCA Protein Assay Kit (ThermoFisher, New South Wales, Australia). Following protein quantification, the tryptic digestion was accomplished by adding sequence grade modified trypsin (Promega-#V5111) to the proteins, for 20 µg of protein 1 µg of trypsin was added to each sample. The protein samples were digested overnight (16 h) at 37 • C (in a heat block) while shaking at 500 g. The tryptic digestion was stopped by adding 20 µL of 5% formic acid in water (vol/vol) to the samples. The desalting procedure was achieved using C18 stage tips (inhouse Whatman ® C18 Paper purchased from Sigma Aldrich). The column was activated using 40 µL of methanol, centrifuged at 1200× g for 2 min and washed with 40 µL of 0.1% formic acid in water. After activating the C18 column, the peptide samples were loaded into the stage tip, centrifuged at 1200× g for 5 min and washed three times with 50 µL of 0.1% formic acid by centrifuging at 1200× g for 2 min. The peptide elution step was achieved by adding 50 µL of 70% acetonitrile and 30% of 0.1% formic acid in the water, centrifuged at 800× g for 5 min, and collected in clean Eppendorf LoBind tubes for further analysis.

DIOS Fabrication
DIOS surfaces were fabricated using phosphorous doped (n-type) monocrystalline (500-550 µm thickness, 0.008-0.02 Ωcm) silicon wafers purchased from Siltronix Silicon Technologies, Archamps, France. The electrochemical etching procedure was carried out by the previously described method [19]. A light-assisted anodic etching was achieved in ethanol: hydrofluoric acid (HF) 1:1 ratio (25% v/v) electrolyte solution. A Teflon cell (2.25 cm diameter) was used to etch the silicon wafer, assembled with the cathode (gold) and anode (platinum) materials. The electrical circuit was activated by generating a density current of 2.24 mA/cm 2 for 3 min using Keithley 2460 SourceMeter (Tektronix Inc., Beaverton, OR, USA). The freshly etched pSi SALDI surface was washed with ethanol and dried under N 2 gas. The pSi surface was oxidised with ozone (0.5 L/min O 2 ) at a flow rate of 5 g/m 3 for 3 min using UV-1 UV-ozone cleaner (SAMCO Inc., Kyoto, Japan). Following oxidation, a pore broadening etch was performed by immersing the porous Si surface in 5% (v/v) HF/H 2 O aqueous solution for 1 min. Subsequently, a second ozone oxidation was performed. The oxidised pSi surfaces were functionalised by adding 90 µL of neat fluorinated silane (1H,1H,2H,2H-perfluorooctyltriethoxysilane) at 80 • C for 60 min. After functionalisation, the porous Si surfaces were washed using acetone and dried under N 2 gas. Following fabrication, a 1 µL of sample was spotted for each sample in triplicate to test performance. Each sample contain approximately 0.3 to 0.4 µg/µL of lipids (based on internal standard lipids)

NIMS Fabrication
A wet electrochemical etching method was used for NIMS fabrication [20]. A monocrystalline (500-550 µm thickness, 0.008-0.02 Ωcm) phosphorus-doped n-type silicon wafers (Siltronix Silicon Technologies, France) was used. Etching employed an electrolyte solution containing 25:200:1 volume ratio of HF/distilled water/surfactant (NCW1001 Wako Pure Chemical Industries, Osaka, Japan). Using a Keithley 2460 current source meter (Tektronix, Inc., OR), a constant current density of 70 mA/cm 2 was applied across the etching cell (area of 7 cm 2 ) for 200 s. The resulting pSi surfaces were then washed rigorously with water followed by ethanol rinsing and dried under N 2 gas. The freshly etched surfaces were ozone-oxidised at 0.5 L/min oxygen at a flow rate of 5 g/m 3 for 30 min using UV-1 UV-ozone cleaner (SAMCO Inc., Kyoto, Japan). The hydroxyl-terminated pSi surfaces were functionalised by adding 90 µL of neat bis-heptadecafluoro-1,1,2,2tetrahydrodecyl)tetramethyldisiloxane (Bis17) at room temperature for 60 min. Following fabrication, a 1 µL of sample was spotted for each sample in triplicate to test surface performance. Each sample contain approximately 0.2 to 0.3 µg/µL of protein (based on BCA assay).

FT-ICR-MS Measurement and Sample Deposition
EVs lipid and peptide spectra were acquired using a Bruker Solarix XR 7T MALDI FT-ICR-MS (Bruker Daltonics, Billerica, MA, USA) equipped with SmartBeam II ultraviolet laser operated in positive ion mode. Data acquisition was performed through imaging analysis on the sample spots to eliminate 'hot-spots' in surface deposition, with a mass range of 200 m/z to 1200 m/z for lipids and from 500 m/z to 4000 m/z for peptides. External calibration using red phosphorus clusters was run prior to each analysis for mass accuracy, assigned as ± 1.5 ppm for peptide analysis and ± 0.6 ppm for lipid analysis. The analyte spots were imaged for 100 µm spatial resolution and analysed in SCiLS Lab software 2019b version (Bruker Daltonics, Germany).
Lithiated cationisation [M + Li] + is a facile method to resolve interference of naturally abundant ions such as Na + and K + , and interpretation of the long-chain base and the fatty acyl substituents of lipids [21]. Initially, a 0.5 mM lithium chloride (LiCl) aqueous solution (w/v) was prepared in HPLC grade methanol and mixed with the 1:1 (v/v) lipid sample. Subsequently, 0.5 µL of the sample mixture was spotted onto a DIOS surface.

Data Processing and Statistics
In this study, we have categorised CRC patients into two groups (i) CRC and (ii) CLM. The data processing was performed in SCiLS lab software (Bruker Daltonics). Mass spectra were processed for baseline subtraction using the iterative convolution algorithm and normalised based on their own total ion count (TIC). The classification model was generated using the linear discriminant analysis algorithm model supported by SCiLS Lab software. Subsequently, a discriminative analysis was performed between (a) CRC vs. CFI and (b) CLM vs. CFI. The receiver operating characteristic (ROC) estimates specificity and sensitivity for threshold classifiers to quantify the diagnostic ability of charged ions that discriminates between sample groups. The top abundant m/z discriminates groups were selected based on the spectral values evaluated from 0.7 to 1 using the area under the ROC curve (AUC value) [22]. The top mass spectral features were selected and exported in CSV format for molecular interpretation (Figure 1, Panel 1).
SCiLS lab software has an inbuilt advanced machine learning algorithm for data pre-processing and filtering-these are peak binning, peak picking, baseline subtraction and post-processing statistical methods. Peptide quantitation was not performed for peptide ions as this type of analysis can be consider to be similar to label-free quantitation. However, before performing trypsin digestion, BCA estimation of protein concentration was performed-showing each sample had 200 µg/mL ± 30 S.D. of protein. The peptide spectral values were incorporated into the MASCOT database for protein identification. The search query for peptide signals were performed by selecting parameters such as Swiss-Prot for database and Homo sapiens within the taxonomy function. In the bottom-up tryptic digestion, carbamidomethylation was selected as a fixed modification (post-translational modification introduced to the cysteine residue), and the variable modification was selected as acetyl protein N-terminal and oxidation (M) residue. The mass accuracy was confirmed based on the monoisotope of each peptide, assigned with ±2.

EVs Characterisation
The EVs size and concentration were determined using NTA, which captured 14.7 ± 0.6 of particles/frame at the concentration of 3.27e +08 ± 1.53e +07 particles/mL, and confirmed that the isolated EVs were on average 125 ± 1 nm in size (Figure 1, Panel 2). TEM characterisation detected EVs sizes ranging between 40 nm and 120 nm, mostly with a spheroid shape. The EVs size detected by NTA is larger (~20% increase in size relative to the average measured using TEM) potentially due to low levels of aggregation between EVs and smaller extracellular vesicles (20-45 nm diameter), which would be retained in the isolation procedure. Sample spheroid-shapes were checked prior to use (Figure 1, Panel 2). Subsequently, the isolated EVs were subjected to SALDI enabled HR-MS for the determination of disease discriminative fingerprints.

EVs Characterisation
The EVs size and concentration were determined using NTA, which captured 14.7 ± 0.6 of particles/frame at the concentration of 3.27 × 10 8 ± 1.53 × 10 7 particles/mL, and confirmed that the isolated EVs were on average 125 ± 1 nm in size (Figure 1, Panel 2). TEM characterisation detected EVs sizes ranging between 40 nm and 120 nm, mostly with a spheroid shape. The EVs size detected by NTA is larger (~20% increase in size relative to the average measured using TEM) potentially due to low levels of aggregation between EVs and smaller extracellular vesicles (20-45 nm diameter), which would be retained in the isolation procedure. Sample spheroid-shapes were checked prior to use (Figure 1, Panel 2). Subsequently, the isolated EVs were subjected to SALDI enabled HR-MS for the determination of disease discriminative fingerprints.

SALDI Surfaces for Lipid and Peptide Detection
Electrochemical anodisation was performed to generate NIMS and DIOS substrates. The average pore size of NIMS substrates was 100 nm the thickness of the porous layer 3.5 µm (Figure 2A,B). The average pore size of DIOS was approximately 120 nm in diameter and 450 nm in-depth ( Figure 2C,D). All analyte spots were dried under a gentle stream of nitrogen before performing MS analysis. The advantage of using NIMS and DIOS is the ease of fabrication and the ability to detect low abundant molecules [23]. Based on previous studies, NIMS performs well to detect peptides in biological samples [19,[23][24][25]. NIMS uses trap liquid initiator material-Bis17, released upon heating by laser irradiation, which carries absorbed peptide molecules. Previously, NIMS has been used to detect peptide hormones, specifically growth hormone-releasing peptide-6 (GHRP-6) and growth hormone-releasing peptide-2 (GHRP-2), in spiked urine substitute (Surine™) [19], at physiologically relevant concentrations. Several studies have used DIOS for the detection of small molecules, such as lipids and metabolites, with ranges <700 Da [23,26]. For instance, Guinan et al. performed metabolite (oxycodone, m/z 316) detection in human saliva and blood using DIOS. The signal intensity ratio obtained by DIOS substrates was larger compared to other substrates such as NIMS and showed excellent sensitivity with detection limits in the low and sub ng/mL range [27].

SALDI Surfaces for Lipid and Peptide Detection
Electrochemical anodisation was performed to generate NIMS and DIOS substrates. The average pore size of NIMS substrates was 100 nm the thickness of the porous layer 3.5 µ m (Figure 2A,B). The average pore size of DIOS was approximately 120 nm in diameter and 450 nm in-depth ( Figure 2C,D). All analyte spots were dried under a gentle stream of nitrogen before performing MS analysis. The advantage of using NIMS and DIOS is the ease of fabrication and the ability to detect low abundant molecules [23]. Based on previous studies, NIMS performs well to detect peptides in biological samples [19,[23][24][25]. NIMS uses trap liquid initiator material-Bis17, released upon heating by laser irradiation, which carries absorbed peptide molecules. Previously, NIMS has been used to detect peptide hormones, specifically growth hormone-releasing peptide-6 (GHRP-6) and growth hormone-releasing peptide-2 (GHRP-2), in spiked urine substitute (Surine™) [19], at physiologically relevant concentrations. Several studies have used DIOS for the detection of small molecules, such as lipids and metabolites, with ranges <700 Da [23,26]. For instance, Guinan et al. performed metabolite (oxycodone, m/z 316) detection in human saliva and blood using DIOS. The signal intensity ratio obtained by DIOS substrates was larger compared to other substrates such as NIMS and showed excellent sensitivity with detection limits in the low and sub ng/mL range [27].  A,B). The pore size of NIMS was estimated between 80 and 100 nm in diameter, and the pore depth of NIMS was 3.5 µ m (B). The average pore size of DIOS was 120 nm, and the average pore depth was 450 nm. The image of the DIOS surface (C,D) was reprinted with permission from Ref. [23]. Copyright (2015), Elsevier.

NIMS-HR-MS for EVs Peptide Mass Fingerprint Identification
NIMS-MS allowed detection of potential peptide signals discriminating CFI and CRC group. Initially, peptide m/z spectral values acquired from the CRC, CLM CFI were statistically compared using the AUC interpretation method as shown in Supplementary Material Figure S1. SCiLS Lab software was used to identify spectral values that discriminate the disease groups, such as (a) CRC compared with CFI and (b) CLM compared with CFI. The linear discriminant analysis algorithm enabled comparative analysis between groups. Subsequently, the AUC method was used to evaluate the diagnostic ability of peptide ions in discriminating sample groups. AUC determined true positive and false positive ions and identified the top ions with AUC values ranging between 0.7 and 1. Subsequently, by means of NIMS we detected 63 peptide ions (Table S1) able to discriminate the CRC and CFI group. For classifying CLM vs. CFI group, via NIMS we detected 56 peptide ions  A,B). The pore size of NIMS was estimated between 80 and 100 nm in diameter, and the pore depth of NIMS was 3.5 µm (B). The average pore size of DIOS was 120 nm, and the average pore depth was 450 nm. The image of the DIOS surface (C,D) was reprinted with permission from Ref. [23]. Copyright (2015), Elsevier.

NIMS-HR-MS for EVs Peptide Mass Fingerprint Identification
NIMS-MS allowed detection of potential peptide signals discriminating CFI and CRC group. Initially, peptide m/z spectral values acquired from the CRC, CLM CFI were statistically compared using the AUC interpretation method as shown in Supplementary Material Figure S1. SCiLS Lab software was used to identify spectral values that discriminate the disease groups, such as (a) CRC compared with CFI and (b) CLM compared with CFI. The linear discriminant analysis algorithm enabled comparative analysis between groups. Subsequently, the AUC method was used to evaluate the diagnostic ability of peptide ions in discriminating sample groups. AUC determined true positive and false positive ions and identified the top ions with AUC values ranging between 0.7 and 1. Subsequently, by means of NIMS we detected 63 peptide ions (Table S1) able to discriminate the CRC and CFI group. For classifying CLM vs. CFI group, via NIMS we detected 56 peptide ions (Table S2). These peptide values were used for peptide sequence matching using MASCOT. MASCOT executes the MOSWE scoring algorithm to rank the top protein hits by comparing 5.6 × 10 5 peptide sequences from the SWISSPROT database and 2.03 × 10 4 sequences from the Homo sapiens (Uniprot ID-UP5640-H-sapiens) database. A panel of the top four putative proteins upregulated in plasma EVs is listed in Supplementary Materials Tables S3 and S4.
Peptide ions with the dominant ion observed at m/z 3408.43 showed a match with the PP2A protein, determined to be a top protein upregulated in our CRC EVs samples ( Figure 3A). Interestingly, evidence has accumulated that PP2A upregulation is strongly associated with the growth of CRC cells, as confirmed in tumour-adjacent tissues collected from patients [28][29][30]. When comparing CLM and CFI samples, peptide ions observed at m/z 1770.98 and m/z 3822.05 were 26% matched with ATF3 protein-determined to be upregulated in CLM EVs ( Figure 3B). (Table S2). These peptide values were used for peptide sequence matching using MAS-COT. MASCOT executes the MOSWE scoring algorithm to rank the top protein hits by comparing 5.6 × 10 5 peptide sequences from the SWISSPROT database and 2.03 × 10 4 sequences from the Homo sapiens (Uniprot ID-UP5640-H-sapiens) database. A panel of the top four putative proteins upregulated in plasma EVs is listed in Supplementary Materials Table S3 and Table S4.
Peptide ions with the dominant ion observed at m/z 3408.43 showed a match with the PP2A protein, determined to be a top protein upregulated in our CRC EVs samples (Figure 3A). Interestingly, evidence has accumulated that PP2A upregulation is strongly associated with the growth of CRC cells, as confirmed in tumour-adjacent tissues collected from patients [28][29][30]. When comparing CLM and CFI samples, peptide ions observed at m/z 1770.98 and m/z 3822.05 were 26% matched with ATF3 protein-determined to be upregulated in CLM EVs ( Figure 3B).

Interpretation of Lipid Species Associated with Metastatic CRC Pathology Using DIOS-FT-ICR-MS
DIOS-MS allowed detection of more than 850 putative lithiated-lipid ions in each sample. As previously mentioned, linear discriminant analysis was performed using the in-built model algorithm in SCiLS Lab software to identify top discriminative ions. The

Interpretation of Lipid Species Associated with Metastatic CRC Pathology Using DIOS-FT-ICR-MS
DIOS-MS allowed detection of more than 850 putative lithiated-lipid ions in each sample. As previously mentioned, linear discriminant analysis was performed using the in-built model algorithm in SCiLS Lab software to identify top discriminative ions. The diagnostic ability of spectral ions was assessed using a threshold AUC (>0.7) to compare ions that allow disease group classification. When compared to CFI group, we identified the top the level of 48 potential lithiated lipid ions intensity was increased in the CRC group, whereas, when compared to CFI the level of top 8 potential lithiated lipid ions intensity was increased in the CLM group. Subsequently, the ions above the AUC threshold were further validated in a publicly available database, LipidMaps. The m/z of precursor ion peak lists were compared against a variety of lipid classes. We observed that 23% of the phosphatidylcholine (PC) subset, 13% of the ceramide subset and 14% of the phosphatidylethanolamine subset were increased in CRC compared to the CFI group. When analysing CLM lipid ions, we observed that 27% of the phosphatidylinositol (PI) subset, 20% of the PG subset and 13% of the cholesterol-based (CL) subset were increased in the CLM compared to the CFI group. The list of identified putative lithiated lipids is shown in Supplementary Materials Tables S5 and S6 Figure 4B shows lithiated lipid peaks identified in the CLM group.
J. Nanotheranostics 2022, 3, FOR PEER REVIEW 10 diagnostic ability of spectral ions was assessed using a threshold AUC (>0.7) to compare ions that allow disease group classification. When compared to CFI group, we identified the top the level of 48 potential lithiated lipid ions intensity was increased in the CRC group, whereas, when compared to CFI the level of top 8 potential lithiated lipid ions intensity was increased in the CLM group. Subsequently, the ions above the AUC threshold were further validated in a publicly available database, LipidMaps. The m/z of precursor ion peak lists were compared against a variety of lipid classes. We observed that 23% of the phosphatidylcholine (PC) subset, 13% of the ceramide subset and 14% of the phosphatidylethanolamine subset were increased in CRC compared to the CFI group. When analysing CLM lipid ions, we observed that 27% of the phosphatidylinositol (PI) subset, 20% of the PG subset and 13% of the cholesterol-based (CL) subset were increased in the CLM compared to the CFI group. The list of identified putative lithiated lipids is shown in Supplementary Materials Table S5 and Table S6.

Discussion
CRC cells release a larger number of EVs compared to healthy cells [31]. These EVs are enriched with tumour regulating signatures, circulating in human blood. Detection of such molecules in a low volume of patient samples is challenging. However, pSi SALDI surfaces such as NIMS and DIOS offer enhanced sensitivity to detect low abundant molecular signatures in blood EVs, useful for rapid and high throughput diagnosis of metastatic CRC progression.
NIMS-HR-MS identified that overexpression of PPA2 protein might be involved in CRC proliferation. The beta regulatory subunit of PP2A has been proposed to modulate catalytic activity and promote programmed cell death by initiating a series of signalling pathway events involved in the execution phase of cell apoptosis [32]. We observed that other EVs proteins, such as Toll-like receptors (TRL), may promote CRC progression in an inflammatory pathway. We have also found that the TLR1 protein is more upregulated in CRC patients, in 76% of the plasma samples, compared to healthy individualssuggesting inflammatory pathways are activated in CRC [33]. Furthermore, we observed that the ATF3 protein is upregulated in CLM EVs. Several studies have proposed that ATF3 functions as a tumour suppressor in CRC and one of the significantly over-represented transcription factors involved in CRC progression [34,35]. A study investigated by Hackl et al. reported that ATF3 expression is upregulated in human CRC tissue compared to healthy individuals [34]. However, the actual mechanism of how ATF3 promotes metastasis is yet to be confirmed. Interestingly, NIMS-HR-MS identified ATF3 protein in the plasma EVs of CLM samples but did not identify significant changes (above the AUC threshold) in the CRC group.
The addition of lithium to the EVs samples reduced mass spectral complexity for lipid identification via DIOS-HR-MS. The results showed an evident shift in the profile of glycerophospholipid and sphingolipids in CRC and CLM groups, who had been diagnosed with dysplasia in the colon. A study conducted by Shen et al. identified several phospholipids, including PG (34:0), lysoPC (18:2), PE (O-36:3), and sphingolipids such as SM (38:8) and Cer (44:5) in plasma EVs as a potential biomarkers for CRC diagnosis [36]. Our observation agrees with this previous study, and we have detected that a wide range of putative lithiated-phospholipids including PG (O-34:0), PC (36:4), PE (O-38:5) and lithiated sphingolipids SM (36:1) and Cer (34:2) were increased in intensity in CRC group plasma EVs. According to the ceramide-sphingosine-S1P rheostat model, both SM and Cer promote apoptosis [37,38]; our results also concur that altered sphingolipid metabolism may contribute to cancer progression. Interestingly, when comparing CLM with CFI group, a significant increase in intensity of CL (68:14) in a CLM group depicted that CL subsets may enhance metastatic CRC progression, possibly via reactive oxidative species and the MAPK signalling pathway [39]. In addition, we could speculate that PI subclasses, upregulated in CLM, modulate phosphatidylinositol-3 kinase (PI3K) enzyme function, which permits the phosphorylation pathway in metastatic progression. Several studies reported that the PI3K pathway is triggered in metastatic CRC progression [40,41]. However, further analyses need to be performed in a larger number of plasma samples to confirm the identified lipids were significantly increased in CRC compared to CFI; and a cross verification of any enzyme activity related to MAPK and PI3K pathway, is still required.
Furthermore, traditional chromatographic MS approaches are difficult to perform at scale in a low volume of biological samples. A panel of putative lipids with a mass tolerance of ±0.005 Da shows that DIOS-HR-MS is useful for profiling low volume samples at speed, enabling hundreds of samples to be profiled in minutes. Although the precise mechanisms of lipids in CRC have not been elucidated, the generation of lithiated ions has allowed us to putatively identify lipids involved in CRC progression, which could be applied to large biobanked sample cohorts.

Conclusions
We have profiled a range of potential CRC biomarkers in <100 µL biobank stored blood samples. Nanostructured pSi SALDI-HR-MS enabled a snapshot of the molecular landscape of CRC progression using a low volume of the patient sample-allowing a chemical description of CRC heterogeneity. Using SALDI-HR-MS we identified putative lipids including PG (O-34:0), PC (36:4), PE (O-38:5), SM (36:1) and Cer (34:2) and proteins such as PP2A and ATF3 that can discriminate disease groups and could act as potential biomarkers for CRC and CLM classification and diagnosis. Moreover, SALDI-HR-MS offers rapid detection of lipids in biological samples without performing time-consuming chromatographic separation and labelling techniques. Based on our results, we expect that SALDI-HR-MS can be expanded to other heterogeneous disease subtype classifications after validation of the corresponding biomarkers.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jnt3040013/s1, Figure S1: Workflow of small extracellular vesicles (EVs) biomarker detection using SALDI-MS for CRC diagnosis. (A) Plasma EVs were isolated from metastatic CRC and CFI individuals. Then trypsin-digestion proteins and lithium adduct lipid samples were spotted on NIMS, and DIOS surfaces, respectively. (B) SALDI surfaces functionalised with a fluorinated silane are then coupled with a high-resolution mass spectrometer. CRC-colorectal cancer stage-I to stage-IV; CFI-cancer free individual and healthy participants; pSi-Porous silicon; NIMS-Nanostructure-initiator mass spectrometry; SALDI-Surface-assisted laser desorption/ionisation mass spectrometry; DIOS-Desorption/ionisation on porous silicon; Table S1: Top 63 peptide ions discriminate CRC and CFI group. CRC-colorectal cancer stage-I to stage-IV; CFI-cancer free individuals and healthy participants; Table S2: Top 56 peptide ions discriminate CLM and CFI group. CLMcolorectal cancer liver metastasis; CFI-cancer free individuals and healthy participants; Table S3: Top 4 discriminative ions identified by NIMS-FT-ICR-MS were applied in the Mascot peptide mass fingerprint for protein matching. We identified the top-five potential protein signatures that can differentiate CRC and CFI group. CRC-colorectal cancer stage-I to stage-IV; CFI-cancer free individuals and healthy participants; NIMS-FT-ICR-MS-Nanostructure-initiator mass spectrometry-Fouriertransform ion cyclotron resonance mass spectrometry; Table S4: Top 4 discriminative ions identified by NIMS-FT-ICR-MS were applied in the Mascot peptide mass fingerprint for the protein match. We identified top-five potential protein signatures that can differentiate CLM and CFI group. CLM-colorectal cancer liver metastasis; CFI-cancer free individuals and healthy participants; NIMS-FT-ICR-MS-Nanostructure-initiator mass spectrometry-Fourier-transform ion cyclotron resonance mass spectrometry; Table S5: Top discriminative ions were identified by DIOS-FT-ICR-MS, which was applied in the LipidMaps database for annotation. We identified a profile of lithiated-lipids that can differentiate CRC from the CFI group. CRC-colorectal cancer stage-I to stage-IV; CFI-cancer free individuals and healthy participants; DIOS-FT-ICR-MS-desorption/ionisation on porous silicon fourier-transform ion cyclotron resonance mass spectrometry. LPE-lysophosphatidylethanolamine, Cer-Ceramide, NAE-N-acylethanolamines, CerP-Ceramide 1-phosphates, LPS-lysophosphatidylserine, PCphosphatidylcholine, PS-phosphatidylserine, LPC-lysophosphatidylcholine, SM-sphingomyelin, PE-phosphatidylethanolamine, DG-diacylglycerol, PG-phosphatidylglycerol, LPGlysophosphatidylglycerol, LPI-lyosphosphatidylionisitol, TG-triacylglycerol; Table S6: DIOS-FT-ICR-MS identified top discriminative ions, annotated using LipidMaps. We identified a profile of lithiated-lipids that can differentiate CLM and CFI group. CLM-colorectal cancer liver metastasis; CFI-cancer free individual and healthy participants; DIOS-FT-ICR-MS-desorption/ionisation on porous silicon fourier-transform ion cyclotron resonance mass spectrometry; PS-phosphatidylserine, PG-phosphatidylglycerol, LPG-lysophosphatidylglycerol, PI-phosphatidylinositol, TGtriacylglycerol, CL-cholesterol, PA-phosphatidicacid